基于实测数据的风电场群汇聚效应研究

发布时间：2018-05-05 15:51

本文选题：大规模风电场群 + 功率波动性　；参考：《东北电力大学》2017年硕士论文

【摘要】：现代社会的生产生活都离不开电力的支持,而随着电力的发展,传统能源的弊端日益明显,主要表现在能源的紧缺和对环境造成的污染。因此,寻找储量丰富的清洁能源是未来电力发展的基础,其中风能源以其丰富的储量和易于获得的特点成为全球发展最为迅速的清洁能源之一。随着我国风电技术的发展,越来越多的风电场投入运行,风电场群逐渐规模化,风电所特有的时空分布差异性在大规模风电场群中得以充分体现,表现为风电场群的总输出功率区别其组成部分的任一风电场,其波动性减弱的现象即为汇聚效应。风电并网需要克服的一点即是风电的波动性,研究风电场群的汇聚效应极具工程利用价值。本文所有的研究分析都以实际工程作为依托。首先从风电功率波动趋势的角度进行汇聚效应的机理分析;接着分别从波动特性和宏观特性的角度对单场和场群的输出功率进行数学描述,通过对比分析,确定汇聚效应的演化趋势;再者建立了一种基于模糊聚类方法的分层汇聚规则,归纳不同层级的风力发电特有的汇聚效应现象及其演化规律;继而通过趋势外推法预测规划目标年输出功率特征值,构建了持续功率曲线的预测模型;最后进行算例分析,验证了汇聚效应的演化规律并证明了预测模型的有效性。本文在对地理数据处理中进行了三维经纬度转化为二维相对位置的处理,使地理数据更适于数学建模以及工程应用。本文为研究汇聚演化规律建立了一种基于模糊聚类方法的分层级汇聚规则,对实际风电场群进行逐层汇聚,从而建立汇聚效应特征值的预测模型。本文提出的数据处理方法和汇聚研究过程更适于实际工程的使用,并经过实例的证明,具有理论价值和现实意义。
[Abstract]:The production and life of modern society can not be separated from the support of electric power. With the development of electric power, the disadvantages of traditional energy are becoming more and more obvious, which are mainly reflected in the shortage of energy and the pollution to the environment. Therefore, finding clean energy with abundant reserves is the basis of the future development of electric power, among which wind energy has become one of the most rapidly developing clean energy sources in the world because of its abundant reserves and easy to obtain. With the development of wind power technology in China, more and more wind farms have been put into operation, and wind farm groups are becoming more and more large-scale. The spatial and temporal distribution differences of wind power have been fully reflected in large-scale wind farm groups. The phenomenon that the total output power of wind farm group distinguishes any wind farm with its component is convergence effect. One thing to overcome in wind power grid connection is the fluctuation of wind power. It is very valuable to study the convergent effect of wind farm cluster. All the research and analysis in this paper are based on the actual project. Firstly, the mechanism of convergent effect is analyzed from the angle of wind power fluctuation trend, and then the output power of single field and field group is described mathematically from the angle of fluctuation characteristic and macroscopic characteristic, and the output power of single field and field group is analyzed by comparison and analysis. Thirdly, a hierarchical clustering rule based on fuzzy clustering method is established to sum up the unique convergence effect phenomenon and its evolution law of wind power generation at different levels. Then, the prediction model of the sustained power curve is constructed by using the trend extrapolation method to predict the output power eigenvalue of the target year. Finally, the evolution law of convergence effect is verified and the validity of the prediction model is proved. In this paper, three dimensional longitude and latitude are transformed into two dimensional relative position in geographic data processing, which makes geographic data more suitable for mathematical modeling and engineering application. In this paper, a hierarchical clustering rule based on fuzzy clustering method is established to study the convergence evolution law, and a prediction model of the characteristic value of convergence effect is established. The data processing method and convergent research process presented in this paper are more suitable for practical engineering and proved to be of theoretical value and practical significance.
【学位授予单位】：东北电力大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TM614

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